Reinforcement learning is a paradigm under which an agent seeks to improve its policy by making learning updates based on the experiences it gathers through interaction with the en...
-- Starting Electronic System Level (ESL) design flows with executable High-Level Models (HLMs) has the potential to sustainably improve productivity. However, writing good HLMs fo...
Christian Zebelein, Joachim Falk, Christian Haubel...
—One of the central areas in network intrusion detection is how to build effective systems that are able to distinguish normal from intrusive traffic. In this paper we explore t...
The amount of legal information is continuously growing. New legislative documents appear everyday in the Web. Legal documents are produced on a daily basis in briefingformat, cont...
To reduce the workload of the driver due to the increasing amount of information and functions, intelligent agents represent a promising possibility to filter the immense data sets...